Asset Correlation Engine for Enterprise Network Tracking
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Solution Overview
Problem
Existing asset tracking systems face challenges in correlating data chunks with varying attributes to the correct assets within an enterprise network, as no single attribute is consistently unique and reliable across all assets, leading to difficulties in identifying and managing assets effectively.
Innovation Solution
The implementation of an asset correlation engine that uses a scoring algorithm with attribute weights to match data chunks with asset entries in a database, creating new entries when no matches are found, and updating attributes to facilitate future matching, while allowing for exclusion rules and fuzzy matching techniques to handle attribute variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single attribute is used to identify assets, then the identification process is simple, but the reliability of asset identification deteriorates because no single attribute is consistently unique and reliable across all assets
Solution Approach 1:
The patent combines multiple attributes (IP address, MAC address, hostname, operating system, etc.) into a composite identification system. The asset correlation engine evaluates multiple attributes simultaneously to generate a confidence score, merging the strengths of different attributes to achieve reliable asset identification without relying on a single potentially unreliable attribute.
Solution Approach 2:
The system creates a universal identification framework that works across diverse asset types and network configurations. By using multiple attributes that can apply to different asset categories (physical devices, virtual machines, cloud resources), the system achieves reliable identification universally rather than requiring asset-specific single attributes.
2Reliability
If multiple attributes are used to identify assets, then the reliability of asset identification improves, but the complexity of correlating data chunks with assets worsens due to varying formats and attribute sets
Solution Approach 1:
The system dynamically adjusts the weight and importance of different attributes based on their reliability and availability in the context. The correlation metric changes parameters (attribute weights, confidence thresholds) to optimize the balance between using multiple attributes for reliability while managing correlation complexity through adaptive parameter adjustment.
Solution Approach 2:
The patent replaces manual or rule-based attribute matching with an automated asset correlation engine that uses a correlation metric and confidence scoring. This substitution of mechanical matching processes with intelligent algorithms reduces the effective complexity of correlating data chunks with assets while maintaining high reliability through multi-attribute evaluation.
3Ease of operation
If assets are tracked using static attributes, then the tracking process is straightforward, but the system becomes outdated when assets are removed, added, or changed
Solution Approach 1:
The system transitions from static attribute tracking to dynamic attribute evaluation. The asset correlation engine continuously receives data chunks and updates asset information in the asset database, allowing the system to adapt to asset changes (additions, removals, modifications) while maintaining straightforward tracking operations through automated updates.
Solution Approach 2:
The patent implements a feedback mechanism where the asset correlation engine continuously monitors incoming data chunks, compares them with existing asset database entries, and updates the database with new or changed asset information. This closed-loop feedback system ensures tracking accuracy is maintained automatically without requiring manual intervention, balancing simplicity with reliability.
Data Source
AI summary
A security management system may be remotely deployed (e.g., using a cloud-based architecture) to add security to an enterprise network. For example, the security management system may scan assets within the enterprise network for vulnerabilities and may receive data from these scans. The security management system may also receive data from other sources, and, as a result, the system may handle data having many different formats and attributes. When the security management system tries to associate data to assets, there may not be a globally unique identifier that is applicable for all received data. Provided in the present disclosure are exemplary techniques for tracking assets across a network using an asset correlation engine that can flexibly correlate data with assets based on attribute information.